The University of Limerick (UL) with over 15,000 students and 1,400 staff is an energetic and enterprising institution with a proud record of innovation and excellence in education, research and scholarship. The dynamic, entrepreneurial and pioneering values which drive UL’s mission and strategy ensures that we capitalise on local, national and international engagement and connectivity. We are renowned for providing an outstanding student experience and conducting leading edge research. Our commitment is to make a difference by shaping the future through educating and empowering our students. UL is situated on a superb riverside campus of over 130 hectares with the River Shannon as a unifying focal point. Outstanding recreational, cultural and sporting facilities further enhance this exceptional learning and research environment.

During the term of the contract the successful applicant will have the opportunity to apply for tenure in accordance with the University's Policy and Procedures for Granting Multi-annual Status to Tenure Track Academic Staff

Salary Scale: Lecturer €52,187 - €83,038 p.a.

Salary Scale: Lecturer below the bar €39,118 - €53,782 p.a.

Further information for applicants and application material is available online.

The closing date for receipt of applications is Monday, 3rd December 2018.

Applications must be completed online before 12 noon, Irish Standard Time on the closing date.

The University of Limerick holds a Bronze Athena SWAN award in recognition of our commitment to advancing equality in higher education. The University is an equal opportunities employer and is committed to selection on merit welcoming applicants from all sections of the community. The University has a range of initiatives to support a family friendly working environment, including flexible working.

“The University of Limerick has implemented a “Smoke and Vape Free Campus Policy”. Smoking and vaping in all forms is prohibited.”

OFFICIAL WEBSITE APPLY
The Siri Search team is creating groundbreaking technology for algorithmic search, machine learning, NLP, and artificial intelligence. The features we build are redefining how hundreds of millions of people use their computers and mobile devices to search and find what they are looking for.

Siri’s universal search engine powers search features across a variety of Apple products, including Siri, Spotlight, Safari, Messages and Lookup. We work with one of the most exciting high performance computing environments, with petabytes of data, millions of queries per second, and have an opportunity to imagine and build products that delight our customers every single day.

Now imagine what you could do at Apple?

Key Qualifications
Industry experience in a Data Science, Machine Learning or Natural Language Processing
Ability to illuminate complex problems with data analysis
Proven product success derived from research and analysis results
Familiarity with Hadoop, Mapreduce and similar technologies
Experience with machine learning models and systems like Tensorflow
Programming language like Python or Go
Experience with Search/Information Retrieval is a plus
Good communication with internal and external teams
Fluency in at least one of French, German, Italian, Spanish
Fluency in English

Description

This role is part of a growing team so we're you will have the opportunity to work in a few areas including Data Science, ML and NLP. Collaborating with team members in Europe and around the world you can work on many areas including:

Perform data mining to support new features - Analyze large datasets to glean actionable insights - Design classifiers and ranking algorithms - Perform language processing and query analysis - Perform ad-hoc statistical analysis - Present results of analysis to team and leadership across Apple - Craft metrics to measure the success of the service

If this is you, we'd love to hear from you.

Education & Experience

MS or Ph.D. in Data Mining, Machine Learning, Statistics, Natural Language Processing (in European languages), Operations Research or related field

Numerical Tours now in ROFFICIAL WEBPAGE
The R tours, that can be browsed as HTML pages, but can also be downloaded as Jupyter notebooks. Please read the installation page for more information about how to run these tours.

The Pattern Analysis and Computer Vision Research Line (PAVIS) at IIT in Genova is looking for a highly qualified post doc with a strong background in Computer Vision, Pattern Recognition and Machine Learning, with particular emphasis on recognition, video analysis, behavior understanding, and prediction. As the activities may be carried out in collaboration with other IIT research units, the previous multidisciplinary experience is an added value which will be duly considered.
The main mission of PAVIS is to design and develop innovative image- and video-based intelligent systems, characterized by the use of highly functional smart sensors and advanced data analytics features. PAVIS also plays an active role in supporting the other IIT research units providing scientists in Neuroscience, Nanophysics and other IIT departments/centers with ad-hoc solutions.
To this end, the group is involved in activities concerning computer vision and pattern recognition, machine learning, multimodal\multimedia data analysis and sensor fusion, and embedded computer vision systems. The lab will pursue this goal by working collaboratively and in cooperation with external private and public partners.

In particular, this call aims at consolidating PAVIS expertise in the video surveillance area and especially on action/activity recognition and scene understanding from video sequences and other sensory modalities.
In particular, the following topics are of interest:
Analysis of static and dynamic scenes.
Recognition (objects, scenes, actions, events, etc.) and reconstruction.
Behavior Analysis and Activity Recognition (individuals, groups, crowd).
Prediction of intentions.
Domain Adaptation.
Multimodal data analysis
Zero-shot Learning

From the methodological standpoint, the ideal candidate should be familiar with one or more of the following subjects (it’s not an exhaustive list): Deep Learning, Graphical Models, Topic Models, Representation/Feature Learning, Sparse and Dictionary Learning, Clustering, Kernel methods, Manifold Learning and Statistical and Probabilistic Models in general.
Candidates to this position have a Ph.D. in Computer Vision, Machine Learning, Pattern Recognition or related areas. Research experience and qualification in computer vision and pattern recognition/machine learning are clearly a must and evidence of top quality research on the above-specified areas in the form of published papers in top conferences/journals and/or patents is mandatory.
Moreover, experience in the preparation and management of research proposals (EU, US, national) and industrial research projects, a few years of postdoc experience, either in academia or in an industrial lab, will also be duly considered. The winning candidate will also be asked to contribute to setting up new (funding) project proposals and will participate in funding activities.
He/she is also expected to publish his/her research results in leading international journals and conferences, supervise Ph.D. candidates and collaborate with other scientists, also with different expertise.
Salary will be commensurate to qualification and experience and in line with international standards.
Further details and informal inquiries can be made by email to pavis@iit.it quoting PAVIS-PD 75470 as the reference number.
Please send your completed application forms by December 31, 2018. The application must include: a curriculum listing all publications (possibly including a pdf of your most representative publications), a research statement describing your previous research experience and outlining its relevance to the above topics and the name of 2 referees by email to pavis@iit.it quoting PAVIS-PD 75470 as the reference number.

IIT was established in 2003 and successfully created a large-scale infrastructure in Genova, a network of 10-state-of-the-art laboratories countrywide and recruited an international staff of about 1100 people from more than 50 countries. IIT's research endeavor focuses on high-tech and innovation, representing the forefront of technology with possible applications from medicine to industry, computer science, robotics, life sciences, and nanobiotechnologies.
We inform you that the information you provide will be used solely for the purposes of evaluating and selecting professional profiles in order to meet the requirements of Istituto Italiano di Tecnologia.
Your data will be processed by Istituto Italiano di Tecnologia, based in Genoa, Via Morego 30, acting as Data Controller, in compliance with the rules on protection of personal data, including those related to data security.
Please also note that, pursuant to articles 15 et. seq. of European Regulation no. 679/2016 (General Data Protection Regulation), you may exercise your rights at any time by contacting the Data Protection Officer (phone +39 010 71781 - email: dpo@iit.it).
Istituto Italiano di Tecnologia is an Equal Opportunity Employer that actively seeks diversity in the workforce.

As for GSI’13, GSI’15 and GSI’17, the objective of this SEE GSI’19 conference, hosted in Toulouse at ENAC, is to bring together pure/applied mathematicians and engineers, with common interest for Geometric tools and their applications for Information analysis.
It emphasizes an active participation of young researchers to discuss emerging areas of collaborative research on “Geometric Science of Information and their Applications”.
Current and ongoing uses of Information Geometry Manifolds in applied mathematics are the following: Advanced Signal/Image/Video Processing, Complex Data Modeling and Analysis, Information Ranking and Retrieval, Coding, Cognitive Systems, Optimal Control, Statistics on Manifolds, Topology/Machine/Deep Learning, Artificial Intelligence, Speech/sound recognition, natural language treatment, Big Data Analytics, Learning for Robotics, etc., which are substantially relevant for industry.
The Conference will be therefore held in areas of topics of mutual interest with the aim to:

Provide an overview on the most recent state-of-the-art

Exchange mathematical information/knowledge/expertise in the area

Identify research areas/applications for future collaboration

This conference will be an interdisciplinary event and will unify skills from Geometry, Probability and Information Theory. Proceedings are published in Springer's Lecture Note in Computer Science (LNCS) series. SPRINGER will sponsor Best paper Award GSI’19.
Gala Diner will take place at Hôtel-Dieu Saint-Jacques in Salle Des Colonnes.

The workshop will bring together experts in geometric mechanics and optimal transport, with emphasis on stochastic aspects. The goal is to explore parallel connections between the two fields such as, for example, the Schrödinger problem and the Monge-Kantorovich theory.

The Team
The Autodesk AI Lab is part of the AI & Robotics group at Autodesk, a rapidly growing team of over 20 researchers and engineers heading up Autodesk’s work in AI, Computational Science and Robotics. This position is based at our scenic Pier-9 AI Lab, on the water next to the Exploratorium in San Francisco.

Job Requirements
A successful candidate should have the following:
• An MS or PhD in a field related to Machine Learning such as: Computer Science,
Mathematics, Statistics or Physics
• Significant doctoral or post-doctoral research experience or 5 or greater years of work
experience
• Solid theoretical background in geometry and geometric methods. e.g. shape analysis,
topology, differential geometry, discrete geometry, functional mapping, etc.•

About the AI Lab
Autodesk is the ideal environment for applying advanced Machine Learning techniques to: learn
from an incredibly rich world of data; predict and synthesize solutions typically beyond human
abilities; and create new levels of automation in how things are physically built. Given the
broad variety of AI problems faced by Autodesk and our clients, we created a centralized facility
to concentrate the research and engineering work behind these solutions ... The Autodesk AI
Lab. The Lab brings together AI Researchers, Software Engineers and specialists in various
problem areas to create novel AI solutions in all the areas mentioned above and more. They
work closely with experts in: geometric modeling, simulation systems, robotics, knowledge
representation, sensing and computer vision, industrial manufacturing and construction
techniques.
The AI Lab works with both product teams and customers to realize these AI solutions, getting
access to massive data streams and seeing our AI models come to life in the field!Responsibilities
As a Principal AI Researcher in the Autodesk AI Lab you will have a range of responsibilities
including:
• Exploring and developing new Machine Learning models and techniques
• Constantly reviewing relevant Machine Learning literature to identify emerging methods
or technologies and current best practices
• Introduce creative approaches to research topics and generates new approaches,
perspectives and solutions to research topics
• Planning and designing research projects: specifying the problem and defining the
project scope.
• Connecting with academics and institutions to build relationships and collaborate
• Realizing solutions through prototypes
• Exploring new data sources and discovering techniques for best leveraging data
• Collecting and performing data analysis to validate and further new theories and
discoveries
• Publishing and talking at conferences
• Working closely with product engineers to design, develop and incorporate AI solutions
into new products
• Meeting with customers to understand how ML could be applied to their problems
• Thinking strategically about research directions
• Mentoring more junior researchers and engineers

Description
The work we do at Autodesk gets to touch nearly every person on the planet. By building tools
for designing buildings, developing machines and even the latest movie, we get to influence
and empower some of the most creative people in the world to solve problems that matter.
We love that very often these are solutions to some of the most pressing issues the world faces:
housing more people, reducing impact on our environment, and dramatically reducing illness
and death in developing parts of the world.
In serving these customers, we get to tap into and realize the potential of the rich streams of
data from those worlds. Perhaps it’s real-time sensor data from cars or 3D scans of buildings
as they are being constructed. In other cases, it’s about learning the language of 3D modeling
from watching designers and then training the future intelligent design tools to make design
more accessible. Or, it’s about automating and refining how things are physically made in the
world, through advanced robotics, other times through controlling 3D printers or sophisticated
milling machines.
This is the ideal environment for applying advanced Machine Learning techniques to: learn from
an incredibly rich world of data; predict and synthesize solutions typically beyond humanabilities; and to create new levels of automation in how things are physically built. Given the
broad variety of AI problems faced by Autodesk we created a centralized facility to concentrate
the research and engineering work behind these solutions ... The Autodesk AI Lab. The Lab
brings together AI Researchers, Software Engineers and specialists in various problem areas to
create novel AI solutions in all the areas mentioned above and more. They work closely with
experts in: geometric modeling, simulation systems, robotics, knowledge representation,
sensing and computer vision, industrial manufacturing and construction techniques.
The AI Lab works with both product teams and customers to realize these AI solutions, getting
access to massive data streams and seeing our AI models come to life in the field!

pyRiemann is a Python machine learning library based on scikit-learn API. It provides a high-level interface for classification and manipulation of multivariate signal through Riemannian Geometry of covariance matrices.

pyRiemann aim at being a generic package for multivariate signal classification but has been designed around applications of biosignal (M/EEG, EMG, etc) classification.

In May 1969 the groundbreaking book of Jean-Marie Souriau appeared,Structure des Systèmes Dynamiques. We will celebrate, in 2019, the jubilee of its publication, with a conference in honour of the work of this great scientist.
Welcome to the conference !

If you want to present a poster, just send us an email with your name, affiliation, the title of your poster and possibly a link on a pdf.

SYLLABUS

In May 1969 the groundbreaking book of Jean-Marie Souriau appeared, Structure des systèmes dynamiques. We will celebrate, in 2019, the jubilee of its publication, with a conference in honour of the work of this great scientist.

The influence of Souriau’s work is felt in the areas he has innovated or developed in his own way. It is important to take stock of it, in particular in order to make the current and future generations aware of his original and deep thought.

The main reasons for organising this conference are the singularity, and at the same time the scope, of the work of Souriau. He was able to create, in his time, a homogeneous group of “Souristes” who for the most part have reached maturity and are able today to convey the originality of this work. It is also time to take stock of the important work to which it has given rise among foreign researchers, many of whom we will invite to speak. The work of Jean-Marie Souriau lives on in different areas of the scientific world and, at different levels of depth, in the development of mathematics and physics, and therefore according to the different temporalities of the history of these disciplines.

All scholars, old and new, recognize this. Souriau’s work is particularly important work for the relationships he has established and developed between physics and geometry. He is one of the most important founders of symplectic geometry, and the theoretical exploitation of his work in this field is far from exhausted.

André Lichnerowicz has said that his work could belong to four international scientific unions: mathematics, mechanics, physics and astronomy. But what interests us is not only Souriau the scientist, but also the philosopher. What is striking is the unity of his thought through the variety of his fields of interest. It is likely true that this thought grows deeper as its areas of application expand. The object of our inquiry will be to analyse his thought insofar as it is related to the philosophy of science and even to pure philosophy.

This conference aims to review the entire work of Jean-Marie Souriau in the five areas in which he worked.

5. Diffeology. Renewal of the formal framework of differential geometry by a stable space category by all natural set operations (i.e. complete, complete, Cartesian closed). This includes highly singular spaces that may not even be separated, infinite dimensional spaces, and so on.

6. Philosophy of Science, Epistemology, History of Science. History of each of the domains evoked (symplectic mechanics, quantification, cosmology and relativity, thermodynamics). In each of these areas Souriau introduced new ideas. These new views have not ceased to be relevant and fruitful. The task of a philosophy of science will be to highlight this novelty.

As far as philosophy is concerned, a new question has been raised about the importance of this work, in its variety and unity, and in its impact on the philosophy of science and philosophy in general, which we propose to deal with in this conference. Souriau’s originality manifested itself in his will and in his attempts to create new languages. We will analyze, in the philosophy section, this important aspect of his work, most evident in his work in geometry and relativity.

A seminar on Topological and Geometrical Structures of Information has been organized at CIRM in 2017, to gather engineers, applied and pure mathematicians interested in the geometry of information. This year FGSI’19 conference will be focused on the foundations of geometric structures of information. It is dedicated to the triumvirat Cartan - Koszul - Souriau and their influence on the field.

The conference will take place in Montpellier from Monday 4th February 2019 at 9am until Wednesday 6th February at 1pm.

Abstract
An overview over recently developed methods for proving decay to equilibrium for dissipative dynamical systems is presented. The methodology is based on Lyapunov functionals, often with the physical interpretation of a (generalized) entropy or free energy.
The course features a short formal introduction to stochastic processes, aimed at an audience with a PDE background. The concepts of martingales and time reversal of homogeneous Markov processes are used to derive local decay results for relative
entropies. These are applied to various examples of Levy processes, including applications in kinetic transport theory, in mathematical biology, and in chemical reaction networks. Quantitative decay results are derived from entropyentropy decay inequalities or from inequalities between entropy decay and its time derivative, i.e. by the celebrated Bakry-Emery approach.
A focus is on hypocoercive problems, where decay to equilibrium holds despite the fact that the decay term for the natural entropy functionals is only semi-denite. Various recent approaches to such problems, mainly in kinetic theory, are compared and unied.
Finally, examples of nonlinear problems are discussed, and the question of structural assumptions allowing for entropy decay is examined.

Information about the research
The Division of Applied Mathematics and Statistics at the Department of Mathematical Sciences at Chalmers University of Technology and the University of Gothenburg, together with the Agrifood and Bioscience unit of RISE Research Institutes of Sweden, invites applications for one two-year postdoctoral position starting November 1, 2018, or as agreed. The successful candidate will be offered a one-year employment at Chalmers, followed by a one-year employment at RISE Agrifood and Bioscience.

The aim of the project is to develop new tools and methods for statistical modeling of random, heterogeneous, porous material structures. This involves both to work with two- and three-dimensional imaging data of real material structures and with simulation of virtual material structures inspired by real materials to understand the connection between structure and mass transport properties (diffusion and flow). The project constitutes part of a collaboration with several major Swedish industries, as well as with experimentalists in academia, and the methods and software that are developed within the project will be applied to real, industry-relevant materials used in for example hygiene products, packaging materials, pharmaceuticals, etc.

As part of the VINNExcellence Centre SuMo Biomaterials (SuMo), the project ‘Material structures seen through microscopy and statistics’ funded by the Swedish Foundation for Strategic Research, and the project ‘Mass transport properties of soft porous granular materials’ funded by the Swedish Research Council, many tools for image analysis, statistical characterization, and generation of virtual material structures have been developed. Further, within the SuMo Centre, state-of-the-art software for lattice Boltzmann-based diffusion and flow simulations is available.

The aim is to build upon the accumulated knowledge from these projects and:

(1) Develop new image analysis and segmentation algorithms for image data. Highly accurate automatic or semi-automatic image analysis methods are crucial for segmentation of imaging data of material structures. This is particularly important for 3D data where data size makes complete manual segmentation very time-consuming.

(3) Perform simulation studies of mass transport properties using available simulation tools developed in related projects together with new methods of generating material structures. Exploring material structures in the computer is important to avoid costly and time-consuming experimental studies.

The goal is a deep understanding of the relationships between microstructure and properties that will benefit both further research and applications.

This position is one of three postdoctoral positions within the new project CoSiMa, which is part of the SuMo Biomaterials centre (www.chalmers.se/sumo).

About the division and the department
At the Division of Applied Mathematics and Statistics we conduct research at a high international level in areas such as biomathematics, bioinformatics, computational mathematics, optimisation, mathematical statistics, kinetic theory. More information about our research groups is available on the website http://www.chalmers.se/en/departments/math/research/research-groups/

We have an international environment with frequent exchanges with other universities around the world. The department provides a friendly, creative, and supportive atmosphere with a steady flow of international guests. At the division there are many committed teachers with extensive and broad experience of all aspects of higher education. Together with the Divisions of Algebra and Geometry and Analysis and Probability we form the academic part of the department of Mathematical Sciences, which is a joint department of Chalmers and the University of Gothenburg, and one of the largest in mathematics in the Nordic countries with a faculty core of about 80. More information about us is available on the website http://www.chalmers.se/en/departments/math/.

At the Agrifood and Bioscience unit at RISE Research Institutes of Sweden we conduct research and development in food, agriculture, and bioscience related topics including quantitative microscopy, image analysis, computational materials science, hetereogeneous and viscoelastic materials, microbiology and food processing. The unit comprises about 100 people, and is part of the division of Bioscience and Materials at RISE Research Institutes of Sweden. More information about us is available on the websitehttp://www.sp.se/en/units/risebiovet/fb/Sidor/default.aspx

Major responsibilities
You are expected to pursue a vigorous research program and collaborate with our researchers.

During the employment at the Department of Mathematical Sciences, we offer you the possibility that up to 20 % of your work may be spent on teaching. RISE Agrifood and Bioscience does not offer teaching.

Position summary
Full-time temporary employment. The position is limited to a maximum of two years (1+1).

Qualifications
You should have a Ph.D. in Applied Mathematics, Mathematical Statistics, Computational Science, possibly also Physics, or equivalent, completed before the starting date of employment and not earlier than three years before the application deadline. Fluency in English is expected. Experience in image analysis and processing, machine learning, spatial statistics, and good programming skills is meriting.

Chalmers continuously strives to be an attractive employer. Equality and diversity are substantial foundations in all activities at Chalmers.

Our offer to you
Chalmers offers a cultivating and inspiring working environment in the dynamic city of Gothenburg.
Read more about working at Chalmers and our benefits for employees.

Application procedure
The application should be marked with Ref 20180454 and written in English. The application should be sent electronically and be attached as pdf-files, as below:

Personal letter: (Please name the document as: Personal letter, Family name, Ref. number) including:
• 1-3 pages where you introduce yourself and present your qualifications.
• Previous research fields and main research results.
• Future goals and research focus. Are there any specific projects and research issues you are primarily interested in?

Other documents:
• Attested copies of completed education, grades and other certificates.

Please use the button at the foot of the page to reach the application form. The files may be compressed (zipped).

*** Chalmers declines to consider all offers of further announcement publishing or other types of support for the recruiting process in connection with this position. ***

Chalmers University of Technology conducts research and education in engineering sciences, architecture, technology-related mathematical sciences, natural and nautical sciences, working in close collaboration with industry and society. The strategy for scientific excellence focuses on our eight Areas of Advance; Building Futures, Energy, Information & Communication Technology, Life Science, Materials Science, Nanoscience & Nanotechnology, Production and Transport. The aim is to make an active contribution to a sustainable future using the basic sciences as a foundation and innovation and entrepreneurship as the central driving forces. Chalmers has around 11,000 students and 3,000 employees. New knowledge and improved technology have characterised Chalmers since its foundation in 1829, completely in accordance with the will of William Chalmers and his motto: Avancez!

The aim of the workshop is to bring together researchers at the junction of discrete random structures, in particular random graphs, random walks, and its applications to complex networks.Poster of the workshop

How to go from the main station Saint-Etienne Chateaucreux to the Institute Camille Jordan: The city bus company: STAS: http://www.reseau-stas.fr/fr/itineraires/4/JourneyPlanner
The Bus line M4 takes you from the main train station (Saint-Etienne Châteaucreux) to the faculty of Sciences.

The School of Advanced Studies (SAS), University of Tyumen, Russia, is recruiting post-
docs and professors in biology, ideally specialized in neurobiology but other profiles will be
considered too. The workload will consist of teaching general undergraduate biology courses
(about 50% of time), and doing research on the neuroscience of consciousness and free will within
an interdisciplinary team (e.g. performing Libet-like experiments using EEG, fMRI etc., available
in Tyumen). If the candidates are not experts in this type of research, they will be given the means
to become experts; they also have the possibility to devote a (small) part of their research to other
personal research in biology. After one successful year, the post-docs will be invited to apply for
a permanent faculty position at the SAS.
The School of Advanced Studies of the University of Tyumen is a new institution, created
in 2017 and incentivized by the Russian Federal Government to become a centre of excellence in
interdisciplinary research and teaching (the students of SAS choose majors in biology, IT,
humanities and social sciences). The scientists we will recruit will receive western-standard
salaries and will have a unique opportunity to develop their own research in neurobiology,
neurophysiology, neuropsychology or related fields, while being offered the possibility to interact
with other disciplines, notably from humanities and social sciences. For info on the general context
of the project: https://sas.utmn.ru/en/free-will-en/. For questions, please contact Dr. Louis
Vervoort at l.vervoort@utmn.ru.
For interested parties, please submit your application via e-mail to l.vervoort [at] utmn.ru.
Include a cover letter (explaining the relevance of your application for these positions), a full CV,
and two letters of recommendation. Applications will be considered from September 1 st 2018
throughout 2018 until the positions are filled; first applications will be given first attention.